1. Field of the Invention
The present invention relates generally to reduction of a high peak-to-average power ratio (PAPR) that is a problem with OFDM (Orthogonal Frequency Division Multiplexing), and in particular, to a partial transmit sequence (PTS) used for PAPR reduction.
2. Description of the Related Art
OFDM is used as a transmission technique for digital broadcasting and will be a significant technology for future high rate multimedia wireless communications. A serious problem with OFDM is high peak power, and present known methods are deficient in providing adequate techniques that result in the reduction of the high peak power.
OFDM is a type of multi-carrier modulation scheme that shows excellent performance in a multi-path fading mobile communication environment. For this reason, OFDM attracts interest as a modulation scheme suitable for ground wave digital video broadcasting (DVB) and digital audio broadcasting (DAB). In this modulation scheme, low rate transmission is performed in parallel on multiple carriers instead of high rate transmission on a single carrier. With parallel transmission, the symbol period of multiple carrier signals is longer than that of original input data. Thus, fading does not focus on a few adjacent bits causing errors but slightly influences a plurality of parallel bits. The robustness to channel fading makes OFDM less sensitive to channel distortion.
OFDM shows a high spectral efficiency because the spectrums of subchannels are orthogonal and overlap each other. Since OFDM modulation/demodulation is implemented by IDFT/DFT (Inverse Discrete Fourier Transform/ Discrete Fourier Transform), efficient digitalization of a modulator/demodulator results. Despite these advantages, OFDM has an inherent shortcoming of a high PAPR in multi-carrier modulation. A signal with a high PAPR decreases the efficiency of a linear amplifier and sets an operational point in a non-linear area for a non-linear amplifier, resulting in mutual modulation between carriers and spectrum distribution. Many methods have been suggested to reduce the PAPR.
The PAPR is defined as                     PAPR        =                                                            max                                  0                  ≤                  n                  ≤                                      N                    -                    1                                                              ⁢                                                                                      s                    ⁡                                          (                      nT                      )                                                                                        2                                                    E              ⁢                              {                                                                                                s                      ⁡                                              (                                                  n                          ⁢                                                                                                          ⁢                          T                                                )                                                                                                  2                                }                                              =                                                    max                                  0                  ≤                  n                  ≤                                      N                    -                    1                                                              ⁢                                                                                      x                    n                                                                    2                                                    E              ⁢                              {                                                                                                x                      n                                                                            2                                }                                                                        (        1        )            where s(nT) is a signal sampled in intervals T, xn is the sample value of the signal, and E{·} is an operator for calculating an expected value.
A basic PAPR reduction method is to operate a linear amplifier in a linear area or to operate a non-linear amplifier in a linear area by use of a back-off. However, this method has the disadvantage of low amplifier efficiency. More simply, clipping can be used whereby if the strength of a signal is greater than a predetermined value, the difference is clipped. Clipping, furthermore, deteriorates BER (Bit Error Rate) performance because of the band distortion caused by non-linear operation. In addition, clipping generates noise in the band, decreasing spectral efficiency.
Coding also can be applied to multiple carriers for the PAPR reduction method. Extra carriers are transmitted with parity bits to reduce the PAPR. This method remarkably reduces the PAPR due to its error correction function and an additional narrow bandwidth. Yet, as more carriers are used, the size of a look-up table or a generation matrix increases, thereby increasing hardware complexity, reducing operation efficiency, and decreasing operational speed.
Two schemes showing promising PAPR reduction have recently been proposed.
One is selective mapping (SLM) and the other is partial transmit sequence (PTS). According to the SLM scheme, data of length N is multiplied by M statistically independent sequences of length N and a sequence with the lowest PAPR is transmitted selectively. Despite the requirement of M IFFT (Inverse Fast Fourier Transform) processes, the SLM scheme can reduce a PAPR greatly and be applied irrespective of the number of carriers.
On the other hand, the PTS scheme, having the advantages of the SLM scheme, is known as the most effective flexible method of reducing the PAPR without non-linear distortion.
FIG. 1 is a conventional block diagram illustrating an apparatus for partial transmit sequence (PTS). As shown in FIG. 1, input data which is input as the unit of length N by a data input block 100, is converted into parallel in the serial-to-parallel converter 110. The output of the serial-to-parallel converter 110 is partitioned into M sub-blocks and assigned to each corresponding carrier having predetermined intervals where “0” is assigned by a certain “0” inserter (not shown) into the rest position in order not to overlap each other by the sub-block partitioner 120. Accordingly, a receiver is able to detect and decode each data block transmitted using the carriers assigned in order not to overlap. Each N-point IFFT 130 is then performed on each data block of length N including both corresponding M sub-block data and “0” values transmitted from the sub-block partitioner 120. The output of each N-point IFFT 130 is optimized and transformed corresponding to phase factors for PAPR by a predetermined optimal algorithm in the optimizer 150. The phase factors are multiplied by the outputs of each N-point IFFT 130 by corresponding multipliers 140. Accordingly, the minimum PAPR can be generated by adding each output of the multipliers multiplied by the output of the corresponding phase factors and N-point IFFTs 130 bit by bit. That is, serial data to be transmitted is divided into data blocks of length N and the data of each data block are distributed in M sub-blocks of length N so that N/M data are assigned to each sub-block with predetermined intervals to avoid overlap, and 0s are filled in the remainder of the sub-blocks.
The PTS scheme applies flexibly according to its sub-block partition methods: interleaved sub-block partition, adjacent sub-block partition, and pseudorandom sub-block partition. According to the interleaved sub-block partition method shown in FIG. 2, carriers are spaced from each other by an identical interval M such that each sub-block is not overlapped with any other sub-block. An input data block of length N is partitioned into M, the number of sub-blocks, and each partitioned data block is assigned to corresponding M sub-block of length N respectfully. As the rest of each M sub-block where the partitioned data is not assigned is to be “0”s, and therefore non-zero data occur in every period of M in the sub-blocks for each N point IFFT, repeatedly. Hence, the Cooley-Tukey IFFT algorithm can be used and as a result, much less computations are required than in the other sub-block partition methods. Yet, the periodicity of non-zero data increases auto-correlation, deteriorating PAPR reduction performance. The required numbers of complex multiplications and additions for the interleaved sub-block partition method is calculated by                                                                         n                mul                            =                                                                    (                                                                                            N                                                      2                            ⁢                            M                                                                          ⁢                                                  log                          2                                                ⁢                                                  N                          M                                                                    +                      N                                        )                                    ×                  M                                =                                                                            N                      2                                        ⁢                                          log                      2                                        ⁢                    L                                    +                  MN                                                                                                                        n                add                            =                                                                    (                                                                                            N                          M                                                ⁢                                                  log                          2                                                ⁢                                                  N                          M                                                                    +                      N                                        )                                    ×                  M                                =                                  N                  ⁢                                                                          ⁢                                      log                    2                                    ⁢                  L                                                                                        (        2        )            where N is the number of carriers where the partitioned data block is assigned (L=N/M) and M is the number of sub-blocks.
In the adjacent sub-block partitioning method shown in FIG. 3, N/M carriers are arranged consecutively with no sub-block overlapping with any other sub-block. Since there is no data periodicity, a typical IFFT algorithm applies. Thus, the adjacent sub-block partitioning method requires a greater volume of computation but shows better performance than the interleaved sub-block partitioning method. The required computation volume for the adjacent sub-block partitioning method is calculated by                                                                         n                mul                            =                                                (                                                            N                      2                                        ⁢                                          log                      2                                        ⁢                    N                                    )                                ×                M                                                                                                        n                add                            =                                                (                                      N                    ⁢                                                                                  ⁢                                          log                      2                                        ⁢                    N                                    )                                ×                M                                                                        (        3        )            
In the pseudorandom sub-block partitioning method shown in FIG. 4, carriers are arranged randomly in each sub-block that does not overlap with any other sub-block. One thing to be noted is that each block is assigned to the same number of carriers. Due to very low auto-correlation, the pseudorandom sub-block partitioning method shows much better PAPR reduction performance than the other two methods, with the same volume of computation as the adjacent sub-block partitioning method.
Table 1 below lists computation volumes for the above three sub-block partitioning methods when N=256 and M varies.
TABLE 1A Comparison between Complex Computation Volumes for ThreeSub-block Partitioning Methods of PTSInterleavedAdjacent, PseudorandomMMultiplicationAdditionMultiplicationAddition 11280204810242048 21408179220484096 41792153640968192 82688128081921638416460810241638432768
FIG. 5 illustrates the PAPR reduction performance for the three sub-block partitioning methods (for reference, CCDF (Complementary Cumulative Distribution Function) represents the probability that PAPR of an OFDM symbol exceeds an arbitrary reference level PAPR0, i.e., CCDF=Pr (PAPR>PAPR0) indicating a probability of the PAPR of an OFDM signal larger than PAPR0). According to FIG. 5, the pseudorandom sub-block partitioning method shows high performance, whereas the interleaved sub-block partitioning method shows low performance, comparitively. Therefore, these three methods are in a trade-off relation in terms of computation volume and performance. Aside from the three methods, there is also a concatenated pseudorandom sub-block partitioning method which is a combination of the interleaved and pseudorandom methods in theory. According to the concatenated pseudorandom sub-block partitioning method, carriers are arranged in an N/C portion of a sub-block (C is a concatenation factor) in the same manner as the pseudorandom sub-block partition method and then the N/C portion of the sub-block is duplicated in the remainder of the data block of length L. As a whole, pseudorandom carrier arrangements are interleaved.
Concerning computation volume and performance, the concatenated pseudorandom sub-block partitioning method is between the interleaved and pseudorandom methods though its computation volume and performance differ depending on the concatenation factor C. The computation volume and performance are in a trade-off relation. Therefore, this concatenated pseudorandom sub-block partitioning method increases the scope of choice for the PTS scheme according to required performance and computation volume.
Since each partitioned data block of length L divided from the input data block of length N is assigned to the corresponding M sub-blocks with “0” values, it increases the number of the optimizing operation as much as M*N and the amount of computation for IFFT. Accordingly, it causes an increase of the high peak-to-average power ratio (PAPR) for the conventional art.